also, for some reason these kind of images (wide, side-by-side) failed to upload (other formats suceeded):
https://demoapp.trains.allegro.ai/projects/215414aaade846db95a9eaac90a9a2d0/experiments/a967de8bd09145ca9e431d96ebb29345/output/log
i'm doing plt.savefig for both of the successful uploads and the failed ones.
I think the only difference is the failed ones use the plt.subplots.
Aren't the two lines enough for you? BTW why lightning and not ignite?
Not so much relevant, since it can be seen from your task 😄 but it would be interesting to find out if trains made something be much slower, and if so - how
But what i meant was an entire project with a well built structure to bases on.. If it uses lightning/ignite/trains for scaling/simplicity reasons - even better (:
There are examples but nothing comes to mind when. Thinking about well fleshed out for Bert etc. Maybe someone here can correct me
i'm using logging.getLogger, tqdm, maybe it's not supported?
yes I cat see that now ^^'
I'm not sure whether the problem can be recreate in the original BERT repo, but i'll try to look into it. never tried to run the original-repo's model/data.
If you can recreate the same problem with the original repo... 🤯 🤩
Hi, I just checked the two lines concept, didn't managed to get normal run-time (supposed to last a minute but it's not progressing) nor the entire logging..
Are you doing imshow or savefig? Is this the matplotlib oop or original subplot? Any warning message relevant to this?
What's your code situation? Is it open enough to allow you to create an issue for this on our GitHub?
All should work, again - is it much slower than without trains?
emm fortunately not (academic thesis which was not published yet), but I can refer to the https://github.com/codertimo/BERT-pytorch I've based on
Looks like it is still running DeliciousSeaanemone40 , you're suggesting it is slower than usual? There are some messages there that I've never seen before
I guess it's not relevant but if it helps:
env settings:
Linux manjaro18 5.4.12-1-MANJARO
Conda env:
Python 3.8.1
torch 1.4